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from smolagents.tools import Tool
import cv2
import numpy as np
import os
def detect_elements(screenshot_path, element_type="table"):
"""
Detect table-like structures or text boxes in a screenshot using OpenCV.
Args:
screenshot_path (str): Path to the screenshot
element_type (str): Type of element to detect ('table', 'textbox') (default: 'table')
Returns:
str: JSON with bounding boxes and detection details
"""
try:
if not os.path.exists(screenshot_path):
return f"Screenshot not found: {screenshot_path}"
# Read and preprocess image
image = cv2.imread(screenshot_path)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)
edges = cv2.Canny(blurred, 50, 150)
# Detect contours
contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
detections = []
for contour in contours:
x, y, w, h = cv2.boundingRect(contour)
area = w * h
aspect_ratio = w / h if h > 0 else 0
# Filter for tables (rectangular, large area)
if element_type == "table" and area > 10000 and 0.5 < aspect_ratio < 2.0:
detections.append({"type": "table", "bbox": [x, y, w, h]})
# Filter for text boxes (narrow, horizontal)
elif element_type == "textbox" and area > 500 and aspect_ratio > 2.0:
detections.append({"type": "textbox", "bbox": [x, y, w, h]})
# Draw bounding boxes on a copy of the image
output_path = screenshot_path.replace(".png", "_detected.png")
output_image = image.copy()
for detection in detections:
x, y, w, h = detection["bbox"]
color = (0, 255, 0) if detection["type"] == "table" else (0, 0, 255)
cv2.rectangle(output_image, (x, y), (x + w, y + h), color, 2)
cv2.imwrite(output_path, output_image)
return json.dumps({
"detections": detections,
"output_image": output_path
}) if detections else "No elements detected"
except Exception as e:
return f"Failed to detect elements: {str(e)}"
# Register the tool
tool = Tool(
name="detect_elements",
description="Detects table-like structures or text boxes in a screenshot using OpenCV.",
inputs={
"screenshot_path": {"type": "str", "description": "Path to the screenshot"},
"element_type": {"type": "str", "default": "table", "description": "Type: 'table' or 'textbox'"}
},
output_type="str",
function=detect_elements
) |